Receiving Method, Apparatus, and System in Cooperative Communications

ABSTRACT

A method includes: demodulating a signal transmitted by a first source end that is received to obtain a first log-likelihood ratio; demodulating a signal transmitted by a second source end that is received to obtain a second log-likelihood ratio; demodulating a signal transmitted by a relay node that is received to obtain a third log-likelihood ratio; based on an exclusive OR feature of network coding, processing the first log-likelihood ratio, the second log-likelihood ratio, and the third log-likelihood ratio to obtain a posterior log-likelihood ratio of the first source end; and decoding the signal transmitted by the first source end that is received by using the posterior log-likelihood ratio of the first source end.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of International Application No.PCT/CN2011/071462, filed on Mar. 2, 2011, which claims priority toChinese Patent Application No. 201010264815.2, filed on Aug. 27, 2010,both of which are hereby incorporated by reference in their entireties.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

REFERENCE TO A MICROFICHE APPENDIX

Not applicable.

TECHNICAL FIELD

The present invention relates to the communications field, and inparticular, to a receiving method, an apparatus, and a system incooperative communications.

BACKGROUND

The idea of cooperative communications is rooted from relaycommunications. In cooperative communications, a user cooperates withother relay nodes to transmit information, ensuring communicationbetween the user and a destination node. Relay-based next-generationnetwork architecture has become the hot spot for research. By usingcooperative transmission technology, it supports direct communicationbetween a source node and a destination node. In addition, byintroducing one or more relay nodes, it allows information sent from thesource node to reach the destination node after being processed by therelay nodes in a certain manner. This multi-hop transmission mannerbypasses obstacles that block electrical wave transmission such asbuildings, overcomes the impact of large-scale fading to a certainextent, reduces path losses between sending and receiving terminals, andlowers the transmit power of the devices, thereby suppressing systeminterference and improving the signal-to-noise ratio of signals. Inaddition, because the destination node may perform receiving processingon signals from different transmitting nodes according to differentcombination manners, cooperative transmission may further apparentlyresist the impact of small-scale fading on channels, improving thetransmission environment for signals to a certain extent and yieldingdifferent diversity gains.

Network coding is an information switching technology that integratesrouting and coding. Its principle is to perform linear or non-linearprocessing on information received from each channel on each node on thenetwork and forward the information to downstream nodes. If networkcoding is used, intermediate nodes on the network do not simply performstorage or forwarding, but encode received information and do not sendthe information, thereby improving the network capacity and robustness.By combining network coding and cooperative communications in an organicmanner, the system performance may be further improved.

In the existing technical solutions for combining network coding andcooperative communications, however, the receiving end uses an estimateobtained by decoding received signals for network decoding. In thismanner, if more than one of the estimates at the receiving end isincorrect, all received information fails to be output through a networkdecoding way. According to the existing technical solutions, networkcoding is not fully utilized to yield diversity gains, and the systemperformance is not high.

SUMMARY

Embodiments of the present invention provide a receiving method, anapparatus, and a system in cooperative communications to obtaindiversity gains by making full use of network coding and improve thesystem performance.

An embodiment of the present invention provides a receiving method incooperative communications. The method includes: demodulating a signaltransmitted by a first source end that is received to obtain a firstlog-likelihood ratio; demodulating a signal transmitted by a secondsource end that is received to obtain a second log-likelihood ratio;demodulating a signal transmitted by a relay node that is received toobtain a third log-likelihood ratio; where, the signal transmitted bythe relay node is a signal obtained after the relay node performsnetwork coding on the signal transmitted by the first source end and thesignal transmitted by the second source end; based on an exclusive ORfeature of network coding, processing the first log-likelihood ratio,the second log-likelihood ratio, and the third log-likelihood ratio toobtain a posterior log-likelihood ratio of the first source end; anddecoding the signal transmitted by the first source end that is receivedby using the posterior log-likelihood ratio of the first source end.

An embodiment of the present invention provides a receiving method incooperative communications. The method includes: demodulating a signaltransmitted by a relay node that is received to obtain a thirdlog-likelihood ratio; where, the signal transmitted by the relay node isa signal obtained after the relay node performs network coding on asignal transmitted by a local end and a signal transmitted by a peerend; based on an exclusive OR feature of network coding, performingjoint processing on the third log-likelihood ratio and the firstlog-likelihood ratio of the local end to obtain a prior log-likelihoodratio of the peer end; where, the first log-likelihood ratio is obtainedin advance according to the signal transmitted by the local end; anddecoding the signal transmitted by the relay node that is received byusing the prior log-likelihood ratio of the peer end to obtain a signaltransmitted by the peer end.

An embodiment of the present invention provides a receiving apparatus incooperative communications. The apparatus includes: a first demodulatingmodule configured to demodulate a signal transmitted by a first sourceend that is received to obtain a first log-likelihood ratio; a seconddemodulating module configured to demodulate a signal transmitted by asecond source end that is received to obtain a second log-likelihoodratio; a third demodulating module configured to demodulate a signaltransmitted by a relay node that is received to obtain a thirdlog-likelihood ratio; where, the signal transmitted by the relay node isa signal obtained after the relay node performs network coding on thesignal transmitted by the first source end and the signal transmitted bythe second source end; a processing module configured to: based on anexclusive OR feature of network coding, process the first log-likelihoodratio, the second log-likelihood ratio, and the third log-likelihoodratio to obtain a posterior log-likelihood ratio of the first sourceend; and a decoding module configured to decode the signal transmittedby the first source end that is received by using the posteriorlog-likelihood ratio of the first source end.

An embodiment of the present invention provides a source end apparatus,including: a likelihood ratio demodulating module configured todemodulate a signal transmitted by a relay node that is received toobtain a third log-likelihood ratio; where, the signal transmitted bythe relay node is a signal obtained after the relay node performsnetwork coding on a signal transmitted by the source end apparatus and asignal transmitted by a peer end of the source end apparatus; alikelihood ratio obtaining module configured to: based on an exclusiveOR feature of network coding, perform joint processing on the thirdlog-likelihood ratio and the first log-likelihood ratio of the sourceend apparatus to obtain a prior log-likelihood ratio of the peer end ofthe source end apparatus; where, the first log-likelihood ratio isobtained in advance according to a signal transmitted by the source endapparatus; and a decoding processing module configured to decode thesignal transmitted by the relay node that is received by using the priorlog-likelihood ratio of the peer end of the source end apparatus toobtain a signal transmitted by the peer end of the source end apparatusto obtain a signal transmitted by the peer end of the source endapparatus.

An embodiment of the present invention provides a cooperationcommunication system, including a first source end, a second source end,a relay node, and a receiving apparatus.

The first source node is configured to transmit a signal to the relaynode and the receiving apparatus.

The second source node is configured to transmit a signal to the relaynode and the receiving apparatus.

The relay node is configured to demodulate received signals transmittedby the first source end and the second source end, perform networkcoding on the two demodulated signals, encode and modulate the signalsafter the network coding, and send them to the receiving apparatus.

The receiving apparatus is configured to: demodulate a signaltransmitted by the first source end that is received to obtain a firstlog-likelihood ratio; demodulate a signal transmitted by the secondsource end that is received to obtain a second log-likelihood ratio;demodulate a signal transmitted by the relay node that is received toobtain a third log-likelihood ratio; based on an exclusive OR feature ofnetwork coding, process the first log-likelihood ratio, the secondlog-likelihood ratio, and the third log-likelihood ratio to obtain aposterior log-likelihood ratio of the first source end; and decode thesignal transmitted by the first source end that is received by using theposterior log-likelihood ratio of the first source end.

According to the technical solutions in the embodiments, for acooperative communications system where a relay node adopts networkcoding, based on the exclusive OR feature of network coding, a posteriorlog-likelihood ratio of a source end or a prior log-likelihood ratio ofa peer end is obtained, and the posterior log-likelihood ratio of thesource end or the prior log-likelihood ratio of the peer end is used todecode received data. In this manner, the characteristics of networkcoding are fully utilized, yielding more diversity gains, and greatlyimproving the system performance.

BRIEF DESCRIPTION OF THE DRAWINGS

To make the technical solutions of the embodiments of the presentinvention or the prior art clearer, the accompanying drawings used inthe description of the embodiments or the prior art are brieflydescribed hereunder. Evidently, the accompanying drawings illustratesome exemplary embodiments of the present invention and persons ofordinary skill in the art may obtain other drawings based on thesedrawings without creative efforts.

FIG. 1 is a schematic structural diagram of a cooperative communicationssystem according to an embodiment of the present invention;

FIG. 2 is a schematic structural diagram of a cooperative communicationssystem according to an embodiment of the present invention;

FIG. 3 is a flow chart of a receiving method in cooperativecommunications according to an embodiment of the present invention;

FIG. 4 is a flow chart of a receiving method in cooperativecommunications according to an embodiment of the present invention;

FIG. 5 a and FIG. 5 b are flow charts of a receiving method incooperative communications according to an embodiment of the presentinvention;

FIG. 6 is a flow chart of a receiving method in cooperativecommunications according to an embodiment of the present invention;

FIG. 7 is a schematic structural diagram of a receiving apparatus incooperative communications according to an embodiment of the presentinvention;

FIG. 8 is a schematic structural diagram of a processing module in areceiving apparatus in cooperative communications according to anembodiment of the present invention;

FIG. 9 is a schematic structural diagram of a processing module in areceiving apparatus in cooperative communications according to anembodiment of the present invention;

FIG. 10 is a schematic structural diagram of a source end apparatusaccording to an embodiment of the present invention;

FIG. 11 is a schematic structural diagram of a cooperativecommunications system according to an embodiment of the presentinvention;

FIG. 12 is a performance simulating diagram of a cooperativecommunications system according to an embodiment of the presentinvention;

FIG. 13 is a performance simulating diagram of a cooperativecommunications system according to an embodiment of the presentinvention; and

FIG. 14 is a schematic structural diagram of a cooperativecommunications system according to an embodiment of the presentinvention.

DETAILED DESCRIPTION

The technical solutions in the embodiments of the present invention arehereinafter described clearly and completely with reference to theaccompanying drawings. Apparently, the described embodiments are onlysome embodiments of the present invention, rather than all theembodiments of the present invention. Based on the embodiments of thepresent invention, all other embodiments obtained by persons of ordinaryskill in the art without making any creative effort shall fall withinthe protection scope of the present invention.

To help persons of ordinary skills in the art better understand thetechnical solutions provided in these embodiments, certain relatedtechnologies are described in the embodiments.

FIG. 1 is a schematic structural diagram of a cooperative communicationssystem according to an embodiment of the present invention. Without lossof generality, two terminals MS1 and MS2, one relay node R, and one basestation BS are considered, where the relay node R helps the terminalscommunicate with the base station. The transmission process is dividedinto two phases. In the first phase, terminals MS1 and MS2 broadcastmessages m₁ and m₂, respectively, to the relay node R and the basestation BS. In the second phase, the relay node R demodulates anddecodes received signals sent by MS1 and MS2, and forwards two decoded)signals to the base station by using a network coding way (that is,m₃=m₁

m₂).

As shown in FIG. 2, after transmission in the two phases, the basestation receives a total of three signals: ym1 received from MS1, ym2from MS2, and ym3 from the relay node R. The BS decodes the threereceived signals to obtain three estimates: {tilde over (m)}₁ {tildeover (m)}₂ {tilde over (m)}₃, and then performs network decoding. If twoestimates are correct, but the other estimate is incorrect, the othersignal may be correctly decoded through a network decoding way. Forexample, if {tilde over (m)}₁ and {tilde over (m)}₃ are correct, but{tilde over (m)}₂ is incorrect, an estimate of the information sent byMS2 may be obtained through a network decoding way {tilde over(m)}₂={tilde over (m)}₁

{tilde over (m)}₃.

If, however, all three signals are decoded incorrectly, no informationmay be correctly output through a network decoding way; if two of thethree signals are decoded incorrectly and the other one is decodedcorrectly, the two signals cannot be correctly decoded through a networkdecoding way. In this manner, according to the technical solution,network coding is not fully utilized to yield diversity gains, and thesystem performance is not high.

As shown in FIG. 3, an embodiment of the present invention provides areceiving method in cooperative communications. The method includes thefollowing steps:

S101: Demodulate a signal transmitted by a first source end that isreceived to obtain a first log-likelihood ratio.

S102: Demodulate a signal transmitted by a second source end that isreceived to obtain a second log-likelihood ratio.

S103: Demodulate a signal transmitted by a relay node that is receivedto obtain a third log-likelihood ratio; where, the signal transmitted bythe relay node is a signal obtained after the relay node performsnetwork coding on the signal transmitted by the first source end and thesignal transmitted by the second source end.

S104: Based on an exclusive OR feature of network coding, process thefirst log-likelihood ratio, the second log-likelihood ratio, and thethird log-likelihood ratio to obtain a posterior log-likelihood ratio ofthe first source end.

S105: Decode the signal transmitted by the first source end that isreceived by using the posterior log-likelihood ratio of the first sourceend.

It should be noted that the process of decoding the signal transmittedby the second source end that is received is similar to the precedingprocess, and is not described herein.

According to the technical solution in the embodiment, for a cooperativecommunications system where a relay node adopts network coding, based onthe exclusive OR feature of network coding, a posterior log-likelihoodratio of a source end is obtained, and the posterior log-likelihoodratio of the source end is used to decode received source end data. Inthis manner, the characteristics of network coding are fully utilized,yielding more diversity gains, and greatly improving the systemperformance.

As shown in FIG. 4, an embodiment of the present invention provides areceiving method in cooperative communications. The method includes thefollowing steps:

S110: Demodulate a signal transmitted by a first source end that isreceived to obtain a first log-likelihood ratio.

S120: Demodulate a signal transmitted by a second source end that isreceived to obtain a second log-likelihood ratio.

S103: Demodulate a signal transmitted by a relay node that is receivedto obtain a third log-likelihood ratio; where, the signal transmitted bythe relay node is a signal obtained after the relay node performsnetwork coding on the signal transmitted by the first source end and thesignal transmitted by the second source end.

S140: Based on an exclusive OR feature of network coding, perform jointprocessing on the second log-likelihood ratio and third log-likelihoodratio to obtain a prior log-likelihood ratio of the first source end.

S150: Combine the prior log-likelihood ratio of the first source end andthe first log-likelihood ratio to obtain a posterior log-likelihoodratio of the first source end.

S160: Decode the signal transmitted by the first source end that isreceived by using the posterior log-likelihood ratio of the first sourceend.

It should be noted that the process of decoding the signal transmittedby the second source end is similar to the process of decoding thesignal transmitted by the first source end. As shown in the dashed boxin FIG. 4, in an embodiment, the method may further include thefollowing:

S170: Based on the exclusive OR feature of network coding, perform jointprocessing on the first log-likelihood ratio and third log-likelihoodratio to obtain a prior log-likelihood ratio of the second source end.

S180: Combine the prior log-likelihood ratio of the second source endand second log-likelihood ratio to obtain a posterior log-likelihoodratio of the second source end.

S190: Decode the signal transmitted by the second source end that isreceived by using the posterior log-likelihood ratio of the secondsource end.

In an embodiment, the technical solution provided in this embodiment maybe called the joint network coding channel decoding solution.

Specifically, according to the method in the embodiment, the detaileddescription is as follows:

In this embodiment, assume that the first log-likelihood ratio isLLR_(m) ₁ , the second log-likelihood ratio is LLR_(m) ₂ , and the thirdlog-likelihood ratio is LLR_(m) ₃ . Make Pr_(ch)(m_(i)=0) indicate theprobability that m_(i)(i=1, 2, 3) is 0, and Pr_(ch)(m_(i)=1) indicatethe probability that m_(i) (i=1, 2, 3) is 1. Apparently,Pr_(ch)(m_(i)=1)=1−Pr_(ch)(m_(i)=0)

m₁ and m₂ indicate the messages broadcast by the first source end andsecond source end, respectively, to the relay node R and base station BSin the first phase, that is, indicate the signal transmitted by thefirst source and the signal transmitted by the second source end,respectively. m₃ indicates the message forwarded by the relay node R byusing a network coding way (that is, m₃=m₁

m₂) to the base station after the relay node demodulates and decodes thereceived signals sent by the first source end and second source end.That is, it is the signal transmitted by the relay node. The specificdescription is as follows:

Demodulate the received data to obtain each log-likelihood ratio LLL_(m)₁ . In this case, according to the definition of log-likelihood ratio,the following is obtained:

$\begin{matrix}\begin{matrix}{{LLR}_{m_{i}} = {\log \left( \frac{\Pr_{ch}\left( {m_{i} = 0} \right)}{\Pr_{ch}\left( {m_{i} = 1} \right)} \right)}} \\{= {{\log \left( \frac{\Pr_{ch}\left( {m_{i} = 0} \right)}{1 - {\Pr_{ch}\left( {m_{i} = 0} \right)}} \right)}\left( {{i = 1},2,3} \right)}}\end{matrix} & (1)\end{matrix}$

Perform logarithm to e at both ends of equation (1) to obtain thefollowing:

$\begin{matrix}{{\Pr_{ch}\left( {m_{i} = 0} \right)} = {\frac{e^{{LLR}_{m_{i}}}}{1 + e^{{LLR}_{m_{i}}}}\left( {{i = 1},2,3} \right)}} & (2)\end{matrix}$

It is easily understood that Pr_(ch)(m_(i)=1)=1−Pr_(ch)(m_(i)=0).

Because m₃ is the message after networking coding is performed on m₁ andm₂, according to the exclusive OR feature between m₁, m₂, and m₃, thefollowing may be obtained:

$\begin{matrix}\begin{matrix}{{\Pr_{ch}^{aprior}\left( {m_{1} = 0} \right)} = {{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{1} = {\left. 0 \middle| m_{3} \right. = 0}} \right)}} +}} \\{{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{1} = {\left. 0 \middle| m_{3} \right. = 1}} \right)}}} \\{= {\frac{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 0}} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 1}} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 0}} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 1}} \right)}}}} \\{= {\frac{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}}}}\end{matrix} & (3)\end{matrix}$

PR_(ch) ^(aprior)(m₁=0) indicates information about the priorprobability that m1 is 0, which is deduced according to the equationm₃=m₁

m₂. Likewise, information about the prior probability that m1 is 1 asdeduced according to the equation m₃=m₁

m₂ is as follows:

$\begin{matrix}\begin{matrix}{{\Pr_{ch}^{aprior}\left( {m_{1} = 1} \right)} = {{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{1} = {\left. 1 \middle| m_{3} \right. = 0}} \right)}} +}} \\{{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{1} = {\left. 1 \middle| m_{3} \right. = 1}} \right)}}} \\{= {\frac{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 1}} \right)}}{{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 1}} \right)}} + {{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 0}} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 1}} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 1}} \right)}}}} \\{= {\frac{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}}}}\end{matrix} & (4)\end{matrix}$

By combining equations (3) and (4), according to the definition of alog-likelihood ratio, the prior log-likelihood ratio of m1 may beobtained as follows:

$\begin{matrix}{{LLR}_{m_{1}}^{aprior} = {\log \left( \frac{\Pr_{ch}^{aprior}\left( {m_{1} = 0} \right)}{\Pr_{ch}^{aprior}\left( {m_{1} = 1} \right)} \right)}} & (5)\end{matrix}$

In this case, put equation (2) into equations (3) and (4). Then put theresults of equations (3) and (4) into equation (5) to obtain the priorlog-likelihood ratio of m1.

Likewise, information about the prior probabilities that m2 is 0 and 1as deduced according to the equation m₃=m₁

m₂ are as shown in equation (6) and equation (7), respectively:

$\begin{matrix}\begin{matrix}{{\Pr_{ch}^{aprior}\left( {m_{2} = 0} \right)} = {{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{2} = {\left. 0 \middle| m_{3} \right. = 0}} \right)}} +}} \\{{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{2} = {\left. 0 \middle| m_{3} \right. = 1}} \right)}}} \\{= {\frac{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 0}} \right)}}{{{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 1}} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 0}} \right)}}{{{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 1}} \right)}}}} \\{= {\frac{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}}{{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}}}\end{matrix} & (6) \\\begin{matrix}{{\Pr_{ch}^{aprior}\left( {m_{2} = 1} \right)} = {{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{2} = {\left. 1 \middle| m_{3} \right. = 0}} \right)}} +}} \\{{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{2} = {\left. 1 \middle| m_{3} \right. = 1}} \right)}}} \\{= {\frac{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 1}} \right)}}{{{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 1}} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 1}} \right)}}{{{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 1}} \right)}}}} \\{= {\frac{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}}{{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}}}\end{matrix} & (7)\end{matrix}$

By combining equations (6) and (7), according to the definition of alog-likelihood ratio, the prior log-likelihood ratio of m2 may beobtained as follows:

$\begin{matrix}{{LLR}_{m_{2}}^{aprior} = {\log \left( \frac{\Pr_{ch}^{aprior}\left( {m_{2} = 0} \right)}{\Pr_{ch}^{aprior}\left( {m_{2} = 1} \right)} \right)}} & (8)\end{matrix}$

Combine the obtained prior log-likelihood ratios of m1 and m2 with theirlog-likelihood ratios after demodulation to obtain posteriorlog-likelihood ratios of m1 and m2.

LLR_(m) _(i) ^(app)=LLR_(m) _(i) +LLR_(m) _(i) ^(aprior)(i=1,2)  (9)

LLR_(m) _(i) ^(app) is called the posterior log-likelihood ratio of m1and m2, which may be used to decode m1 and m2.

As shown in FIG. 12, this embodiment simulates the system performancewhen the receiving method in cooperative communications is used. Thesimulation test is based on the Matlab simulation platform, where theTurbo code in Long Term Evolution (LTE) is used, the length of anencoding block is 1024 bytes, the maximum number of iteration times inTurbo decoding is 5, and Rayleigh fading channels are used. As shown inFIG. 12, compared with the existing technical solutions, the technicalsolution (joint network coding channel decoding solution) of using themethod in this embodiment yields a gain of almost 4.3 dB when the systembit error rate (BER) is 10-2. The effects are obvious.

According to the technical solutions in the embodiments, for acooperative communications system where a relay node adopts networkcoding, based on the exclusive OR feature of network coding, a priorlog-likelihood ratio of a source end is obtained, the priorlog-likelihood ratio of the source end and a log-likelihood ratio of thesource end obtained through demodulation are combined to obtain aposterior log-likelihood ratio of the source end, and then the posteriorlog-likelihood ratio of the source end is used to decode received sourceend data. In this manner, the characteristics of network coding arefully utilized, yielding more diversity gains, and greatly improving thesystem performance.

As shown in FIG. 5, an embodiment of the present invention provides areceiving method in cooperative communications. The method includes thefollowing steps:

S210: Demodulate a signal transmitted by a first source end that isreceived to obtain a first log-likelihood ratio.

S220: Demodulate a signal transmitted by a second source end that isreceived to obtain a second log-likelihood ratio.

S230: Demodulate a signal transmitted by a relay node that is receivedto obtain a third log-likelihood ratio; where, the signal transmitted bythe relay node is a signal obtained after the relay node performsnetwork coding on the signal transmitted by the first source end and thesignal transmitted by the second source end.

S240: Based on an exclusive OR feature of network coding, perform jointprocessing on the first log-likelihood ratio and the thirdlog-likelihood ratio to obtain a prior log-likelihood ratio of thesecond source end.

S250: Combine the prior log-likelihood ratio of the second source endand the second log-likelihood ratio to obtain a posterior log-likelihoodratio of the second source end.

S260: Based on the exclusive OR feature of network coding, perform jointprocessing on the posterior log-likelihood ratio of the second sourceend and the third log-likelihood ratio to obtain a prior log-likelihoodratio of the first source end.

S270: Combine the prior log-likelihood ratio of the first source end andthe first log-likelihood ratio to obtain a posterior log-likelihoodratio of the first source end.

S280: Decode the signal transmitted by the first source end that isreceived by using the posterior log-likelihood ratio of the first sourceend.

It should be noted that the process of decoding the signal from thesecond source end is similar to the process of decoding the signal fromthe first source end. As shown in the dashed box in FIG. 5, in anembodiment, the method may further include the following:

S290: Based on the exclusive OR feature of network coding, perform jointprocessing on the second log-likelihood ratio and the thirdlog-likelihood ratio to obtain a prior log-likelihood ratio of the firstsource end.

S291: Combine the prior log-likelihood ratio of the first source end andthe first log-likelihood ratio to obtain a posterior log-likelihoodratio of the first source end.

S292: Based on the exclusive OR feature of network coding, perform jointprocessing on the posterior log-likelihood ratio of the first source endand the third log-likelihood ratio to obtain a prior log-likelihoodratio of the second source end.

S293: Combine the prior log-likelihood ratio of the second source endand the second log-likelihood ratio to obtain a posterior log-likelihoodratio of the second source end.

S294: Decode the signal transmitted by the second source end that isreceived by using the posterior log-likelihood ratio of the secondsource end.

In an embodiment, the technical solution provided in this embodiment maybe called the iterative joint network coding channel decoding solution.

Specifically, according to the method in the embodiment, the detaileddescription is as follows:

In this embodiment, assume that the first log-likelihood ratio isLLR_(m) ₁ , the second log-likelihood ratio is LLR_(m) ₂ , and the thirdlog-likelihood ratio is LLR_(m) ₃ . Make Pr_(ch) (m_(i)=0) indicate theprobability that m_(i)(i=1, 2, 3) is 0, and Pr_(ch)(m_(i)=1) indicatethe probability that m_(i)(i=1, 2, 3) is 1. Apparently,Pr_(ch)(m_(i)=1)=1−Pr_(ch)(m_(i)=0).

m₁ and m₂ indicate the messages broadcast by the first source end andsecond source end, respectively, to the relay node R and base station BSin the first phase, that is, indicate the signal transmitted by thefirst source and the signal transmitted by the second source end. m₃indicates the message forwarded by the relay node R by using a networkcoding way (that is, m₃=m₁

m₂) to the base station after the relay node demodulates and decodes thereceived signals sent by the first source end and second source end.That is, it is the signal transmitted by the relay node. The specificdescription is as follows:

Demodulate the received data to obtain each log-likelihood ratio LLR_(m)_(i) . In this case, according to the definition of a log-likelihoodratio, the following is obtained:

$\begin{matrix}\begin{matrix}{{LLR}_{m_{i}} = {\log \left( \frac{\Pr_{ch}\left( {m_{i} = 0} \right)}{\Pr_{ch}\left( {m_{i} = 1} \right)} \right)}} \\{= {{\log \left( \frac{\Pr_{ch}\left( {m_{i} = 0} \right)}{1 - {\Pr_{ch}\left( {m_{i} = 0} \right)}} \right)}\left( {{i = 1},2,3} \right)}}\end{matrix} & (10)\end{matrix}$

Perform logarithm to e at both ends of equation (10) to obtain thefollowing:

$\begin{matrix}{{\Pr_{ch}\left( {m_{i} = 0} \right)} = {\frac{^{{LLR}_{m_{i}}}}{1 + ^{{LLR}_{m_{i}}}}\left( {{i = 1},2,3} \right)}} & (11)\end{matrix}$

It is easily understood that Pr_(ch)(m_(i)=1)=1−Pr_(ch)(m_(i)=0).

As m₃ is the message after networking coding for m₁ and m₂, according tothe exclusive OR feature between m₁, m₂, and m₃, the following may beobtained:

$\begin{matrix}\begin{matrix}{{\Pr_{ch}^{aprior}\left( {m_{1} = 0} \right)} = {{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{1} = {\left. 0 \middle| m_{3} \right. = 0}} \right)}} +}} \\{{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{1} = {\left. 0 \middle| m_{3} \right. = 1}} \right)}}} \\{= {\frac{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 0}} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 1}} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 0}} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 1}} \right)}}}} \\{= {\frac{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}}}}\end{matrix} & (12)\end{matrix}$

Pr_(ch) ^(aprior)(m₁=0) indicates information about the priorprobability that m1 is 0, which is deduced according to the equationm₃=m₁

m₂. Likewise, information about the prior probability that m1 is 1 asdeduced according to the equation m₃=m₁

m₂ is as follows:

$\begin{matrix}\begin{matrix}{{\Pr_{ch}^{aprior}\left( {m_{1} = 1} \right)} = {{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{1} = {\left. 1 \middle| m_{3} \right. = 0}} \right)}} +}} \\{{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{1} = {\left. 1 \middle| m_{3} \right. = 1}} \right)}}} \\{= {\frac{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 1}} \right)}}{{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 1}} \right)}} + {{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{1} \right. = 0}} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 1}} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{1} \right. = 1}} \right)}}}} \\{= {\frac{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}}}}\end{matrix} & (13)\end{matrix}$

By combining equations (12) and (13), according to the definition of alog-likelihood ratio, the prior log-likelihood ratio of m1 may beobtained as follows:

$\begin{matrix}{{LLR}_{m_{1}}^{aprior} = {\log \left( \frac{\Pr_{ch}^{aprior}\left( {m_{1} = 0} \right)}{\Pr_{ch}^{aprior}\left( {m_{1} = 1} \right)} \right)}} & (14)\end{matrix}$

Combine the obtained prior log-likelihood ratio of m1 with itslog-likelihood ratio after demodulation to obtain a posteriorlog-likelihood ratio of m1.

LLR_(m) ₁ ^(app)=LLR_(m) ₁ +LLR_(m) ₁ ^(aprior)(i=1,2)  (15)

Calculate LLR_(m) ₁ by using the posterior log-likelihood ratio of m1obtained in equation (15). Then obtain new Pr_(ch)(m₁=0) andPr_(ch)(m₁=1) according to equation (11). The information about priorprobabilities that m2 is 0 and 1 as deduced according to m₃=m₁

m₂ is shown in equation (16) and equation (17), respectively:

$\begin{matrix}\begin{matrix}{{\Pr_{ch}^{aprior}\left( {m_{2} = 0} \right)} = {{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{2} = {\left. 0 \middle| m_{3} \right. = 0}} \right)}} +}} \\{{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{2} = {\left. 0 \middle| m_{3} \right. = 1}} \right)}}} \\{= {\frac{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 0}} \right)}}{{{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 1}} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 0}} \right)}}{{{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 1}} \right)}}}} \\{= {\frac{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}}{{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}}}\end{matrix} & (16) \\\begin{matrix}{{\Pr_{ch}^{aprior}\left( {m_{2} = 1} \right)} = {{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{2} = {\left. 1 \middle| m_{3} \right. = 0}} \right)}} +}} \\{{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{2} = {\left. 1 \middle| m_{3} \right. = 1}} \right)}}} \\{= {\frac{{\Pr_{ch}\left( {m_{3} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 1}} \right)}}{{{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 0 \middle| m_{2} \right. = 1}} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{3} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 1}} \right)}}{{{\Pr_{ch}\left( {m_{2} = 0} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 0}} \right)}} + {{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = {\left. 1 \middle| m_{2} \right. = 1}} \right)}}}} \\{= {\frac{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}} +}} \\{\frac{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}}{{{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{2} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{2} = 1} \right)}}}}\end{matrix} & (17)\end{matrix}$

By combining equations (16) and (17), according to the definition oflog-likelihood ratio, the prior log-likelihood ratio of m2 may beobtained as follows:

$\begin{matrix}{{LLR}_{m_{2}}^{aprior} = {\log \left( \frac{\Pr_{ch}^{aprior}\left( {m_{2} = 0} \right)}{\Pr_{ch}^{aprior}\left( {m_{2} = 1} \right)} \right)}} & (18)\end{matrix}$

Put Pr_(ch)(m₁=0), Pr_(ch)(m₁=1), Pr_(ch)(m₂=0), Pr_(ch)(m₂=1), andPr_(ch)(m₃=1) obtained according to equation (11) into equations (16)and (17), and then put the calculation results of equations (16) and(17) into equation (18) to obtain the prior log-likelihood ratio of m2.

Combine the obtained prior log-likelihood ratio of m2 with itslog-likelihood ratio after demodulation to obtain a posteriorlog-likelihood ratio of m2.

LLR_(m) ₂ ^(app)=LLR_(m) ₂ +LLR_(m) ₂ ^(aprior)(i=1,2)  (19)

It is easily understood that the posterior log-likelihood ratio of m1may also be obtained according to a process similar to the precedingone, and the process is not described herein.

Enter the obtained posterior log-likelihood ratios of m1 and m2 to adecoder for decoding.

As shown in FIG. 13, this embodiment simulates the system performancewhen the receiving method in cooperative communications is used. Thesimulation test is based on the Matlab simulation platform, where Turbocode in LTE is used, the length of an encoding block is 1024 bytes, themaximum number of iteration times in Turbo decoding is 5, and Rayleighfading channels are used. As shown in FIG. 13, compared with theexisting technical solutions, the technical solution (iterative jointnetwork coding channel decoding solution) of using the method in thisembodiment yields a gain of almost 4.5 dB when the system BER is 10-2.The effects are obvious. In addition, compared with the joint networkcoding channel decoding solution (non-iterative), the iterative jointnetwork coding channel decoding solution according to this embodimentachieves a lower system BER (the BER simulation curve in the iterativesolution is below the BER simulation curve in the non-iterativesolution), further improving the system performance.

According to the technical solutions in the embodiments, for acooperative communications system where a relay node adopts networkcoding, based on the exclusive OR feature of network coding, a priorlog-likelihood ratio of a source end is obtained, the priorlog-likelihood ratio of the source end and a log-likelihood ratio of thesource end obtained through demodulation are combined to obtain aposterior log-likelihood ratio of the source end, a posteriorlog-likelihood ratio of another source end is obtained through iterativecalculation of the posterior log-likelihood ratio of the source end, andthen the posterior log-likelihood ratio of the another source end isused to decode received data of the another source end. In this manner,the characteristics of network coding are fully utilized, yielding morediversity gains, and greatly improving the system performance.

As shown in FIG. 6, an embodiment of the present invention provides areceiving method in cooperative communications. The method includes thefollowing steps:

S300: Demodulate a signal transmitted by a relay node that is receivedto obtain a third log-likelihood ratio; where, the signal transmitted bythe relay node is a signal obtained after the relay node performsnetwork coding on a signal transmitted by a local end and a signaltransmitted by a peer end.

It should be noted that the local end in this embodiment refers to anapparatus for executing the method in this embodiment, and may be aterminal or a base station. The peer end is relative to the local end(the apparatus for executing the method in this embodiment).

S301: Based on an exclusive OR feature of network coding, perform jointprocessing on the third log-likelihood ratio and a first log-likelihoodratio of the local end to obtain a prior log-likelihood ratio of thepeer end; where, the first log-likelihood ratio is known, and may beobtained in advance according to the signal transmitted by the localend.

S302: Decode the signal transmitted by the relay node that is receivedby using the prior log-likelihood ratio of the peer end to obtain asignal transmitted by the peer end.

In an embodiment, the receiving method in cooperative communicationscorresponding to FIG. 6 may be used in the cooperative communicationssystem shown in FIG. 14. Specifically, according to the method in theembodiment, based on the application system scenario in FIG. 14, thedetailed description is as follows:

In this embodiment, assume that the first log-likelihood ratio isLLR_(m) ₁ , and the third log-likelihood ratio is LLR_(m) ₃ . MakePR_(ch)(m_(i)=0) indicate the probability that m_(i)(i=1, 2, 3) is 0,and Pr_(ch)(m_(i)=1) indicate the probability that m_(i)(i=1, 2, 3)is 1. Apparently Pr_(ch)(m_(i)=1)=1−Pr_(ch)(m_(i)=0).

m₁ indicates the message transmitted by the local end (a local endapparatus 50) in the first phase to the relay node R (a relay node 60),that is, the signal transmitted by the local end; m₂ indicates themessage transmitted by the peer end (a peer end apparatus 70) in thesecond phase to the relay node R (a relay node 60), that is, the signaltransmitted by the peer end; m₃ indicates the message forwarded by therelay node R by using a network coding way (that is, m₃=m₁

m₂) to the local end and peer end after the relay node demodulates anddecodes the received signals sent by the local end and peer end, thatis, the signal transmitted by the relay node.

Corresponding to the preceding embodiment, the processing method isdescribed as follows:

After receiving the signal that is forwarded by the relay node and hasundergone the network coding, the local end demodulates the signal, andrecords the log-likelihood ratio after demodulation as LLR_(m) ₃ (thethird log-likelihood ratio).

According to network decoding, because m₂=m₁

m₃, there are two cases in which m₂ is 0, that is, when m₁ and m₃ areboth 0, and when m₁ and m₃ are both 1. There are two cases in which m₂is 1, that is, when m₁=0 and m₃=1, and when m₁=1 and m₃=0. Therefore,the prior likelihood ratio (second likelihood ratio) of m₂ (that is, thesignal transmitted by the peer end) is as follows:

$\begin{matrix}\begin{matrix}{{LLR}_{m_{2}}^{aprior} = {\log \left( \frac{\Pr_{ch}^{aprior}\left( {m_{2} = 0} \right)}{\Pr_{ch}^{aprior}\left( {m_{2} = 1} \right)} \right)}} \\{= {\log \left( \frac{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 1} \right)}} + {{\Pr_{ch}\left( {m_{1} = 1} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}}} \right)}} \\{= {\log \left( \frac{{{\Pr_{ch}\left( {m_{1} = 0} \right)}{\Pr_{ch}\left( {m_{3} = 0} \right)}} + {\left( {1 - {\Pr_{ch}\left( {m_{1} = 0} \right)}} \right)\left( {1 - {\Pr_{ch}\left( {m_{3} = 0} \right)}} \right)}}{{{\Pr_{ch}\left( {m_{1} = 0} \right)}\left( {1 - {\Pr_{ch}\left( {m_{3} = 0} \right)}} \right)} + {\left( {1 - {\Pr_{ch}\left( {m_{1} = 0} \right)}} \right){\Pr_{ch}\left( {m_{3} = 0} \right)}}} \right)}} \\{= {\log \left( \frac{{\left( \frac{^{{LLR}_{m_{1}}}}{1 + ^{{LLR}_{m_{1}}}} \right)\left( \frac{^{{LLR}_{m_{3}}}}{1 + ^{{LLR}_{m_{3}}}} \right)} + {\left( {1 - \frac{^{{LLR}_{m_{1}}}}{1 + ^{{LLR}_{m_{1}}}}} \right)\left( {1 - \frac{^{{LLR}_{m_{3}}}}{1 + ^{{LLR}_{m_{3}}}}} \right)}}{{\left( \frac{^{{LLR}_{m_{1}}}}{1 + ^{{LLR}_{m_{1}}}} \right)\left( {1 - \frac{^{{LLR}_{m_{3}}}}{1 + ^{{LLR}_{m_{3}}}}} \right)} + {\left( {1 - \frac{^{{LLR}_{m_{1}}}}{1 + ^{{LLR}_{m_{1}}}}} \right)\left( \frac{^{{LLR}_{m_{3}}}}{1 + ^{{LLR}_{m_{3}}}} \right)}} \right)}} \\{= {\log \left( \frac{1 + ^{{LLR}_{m_{1}} + {LLR}_{m_{3}}}}{^{{LLR}_{m_{1} + ^{{LLR}_{m_{3}}}}}} \right)}}\end{matrix} & (11)\end{matrix}$

In this embodiment, because m₁ is known to the local end, the firstlog-likelihood ratio LLR_(m) ₁ may be expressed as follows:

$\begin{matrix}{{LLR}_{m\; 1} = \left\{ \begin{matrix}{\beta,{{{if}\mspace{14mu} m_{1}} = 1}} \\{{- \beta},{{{if}\mspace{14mu} m_{1}} = 0}}\end{matrix} \right.} & (12)\end{matrix}$

Here, β may be a positive real number. In an embodiment, the value of βmay be 10. Certainly, in another embodiment, it may be 8. In stillanother embodiment, it may further be 6. The embodiments of the presentinvention do not restrict the value of β.

Put equation (12) and the third log-likelihood ratio obtained byperforming demodulation into equation (11) to obtain the priorlog-likelihood ratio (the second prior log-likelihood ratio) of the peerend.

Decode the signal transmitted by the relay node that is received byusing the obtained prior log-likelihood ratio (second priorlog-likelihood ratio) of the second source end. Then the m₂ messagetransmitted by the peer end may be obtained.

According to the technical solution in the embodiment, for a cooperativecommunications system where a relay node adopts network coding, aposterior log-likelihood ratio of a peer end is obtained based on theexclusive OR feature of network coding, and the posterior log-likelihoodratio of the peer end is used to decode received data. In this manner,the characteristics of network coding are fully utilized, yielding morediversity gains, and greatly improving the system performance.

As shown in FIG. 7, an embodiment of the present invention provides areceiving apparatus in cooperative communications. The apparatusincludes: a first demodulating module 310 configured to demodulate asignal transmitted by a first source end that is received to obtain afirst log-likelihood ratio; a second demodulating module 320 configuredto demodulate a signal transmitted by a second source end that isreceived to obtain a second log-likelihood ratio; a third demodulatingmodule 330 configured to demodulate a signal transmitted by a relay nodethat is received to obtain a third log-likelihood ratio; where, thesignal transmitted by the relay node is a signal obtained after therelay node performs network coding on the signal transmitted by thefirst source end and the signal transmitted by the second source end; aprocessing module 340 configured to: based on an exclusive OR feature ofnetwork coding, process the first log-likelihood ratio, the secondlog-likelihood ratio, and the third log-likelihood ratio to obtain aposterior log-likelihood ratio of the first source end; and a decodingmodule 350 configured to decode the signal transmitted by the firstsource end that is received by using the posterior log-likelihood ratioof the first source end obtained by the processing module 340.

It should be noted that the processing module 340 may further beconfigured to: based on the exclusive OR feature of network coding,process the first log-likelihood ratio, the second log-likelihood ratio,and the third log-likelihood ratio to obtain a posterior log-likelihoodratio of the second source end; and the decoding module 350 may furtherbe configured to decode the signal transmitted by the second source endthat is received by using the posterior log-likelihood ratio of thesecond source end obtained by the processing module 340.

According to the technical solution in the embodiment, for a cooperativecommunications system where a relay node adopts network coding, based onthe exclusive OR feature of network coding, a posterior log-likelihoodratio of a source end is obtained, and the posterior log-likelihoodratio of the source end is used to decode received source end data. Inthis manner, the characteristics of network coding are fully utilized,yielding more diversity gains, and greatly improving the systemperformance.

As shown in FIG. 8, in an embodiment, the processing module 340 mayinclude: a first processing unit 341 configured to: based on theexclusive OR feature of network coding, perform joint processing on thesecond log-likelihood ratio and third log-likelihood ratio to obtain aprior log-likelihood ratio of the first source end;

The specific processing and calculation procedures of the firstprocessing unit 341 are described in the method embodiment, and are notdescribed herein.

A second processing unit 342 is configured to combine the priorlog-likelihood ratio of the first source end and first log-likelihoodratio to obtain a posterior log-likelihood ratio of the first sourceend.

The specific processing and calculation procedures of the secondprocessing unit 342 are described in the method embodiment, and are notdescribed herein.

According to the technical solutions in the embodiments, for acooperative communications system where a relay node adopts networkcoding, based on the exclusive OR feature of network coding, a priorlog-likelihood ratio of a source end is obtained, the priorlog-likelihood ratio of the source end and a log-likelihood ratio of thesource end obtained through demodulation are combined to obtain aposterior log-likelihood ratio of the source end, and then the posteriorlog-likelihood ratio of the source end is used to decode received sourceend data. In this manner, the characteristics of network coding arefully utilized, yielding more diversity gains, and greatly improving thesystem performance.

As shown in FIG. 9, in an embodiment, the processing module 340 mayfurther include: a third processing unit 343 configured to: based on theexclusive OR feature of network coding, perform joint processing on thefirst log-likelihood ratio and third log-likelihood ratio to obtain aprior log-likelihood ratio of the second source end. The specificprocessing and calculation procedures of the third processing unit 343are described in the method embodiment, and are not described herein.

A fourth processing unit 344 is configured to combine the priorlog-likelihood ratio of the second source end and second log-likelihoodratio to obtain a posterior log-likelihood ratio of the second sourceend.

The specific processing and calculation procedures of the fourthprocessing unit 344 are described in the method embodiment, and are notdescribed herein.

A fifth processing unit 345 is configured to: based on the exclusive ORfeature of network coding, perform joint processing on the posteriorlog-likelihood ratio of the second source end and third log-likelihoodratio to obtain a prior log-likelihood ratio of the first source end.

The specific processing and calculation procedures of the fifthprocessing unit 345 are described in the method embodiment, and are notdescribed herein.

A sixth processing unit 346 is configured to combine the priorlog-likelihood ratio of the first source end and first log-likelihoodratio to obtain a posterior log-likelihood ratio of the first sourceend.

The specific processing and calculation procedures of the sixthprocessing unit 346 are described in the method embodiment, and are notdescribed herein.

It should be noted that the processing apparatus in cooperativecommunications may be a base station in an embodiment, or a terminal inanother embodiment.

According to the technical solutions in the embodiments, for acooperative communications system where a relay node adopts networkcoding, based on the exclusive OR feature of network coding, a priorlog-likelihood ratio of a source end is obtained, the priorlog-likelihood ratio of the source end and a log-likelihood ratio of thesource end obtained through demodulation are combined to obtain aposterior log-likelihood ratio of the source end, a posteriorlog-likelihood ratio of another source end is obtained through iterativecalculation of the posterior log-likelihood ratio of the source end, andthen the posterior log-likelihood ratio of the another source end isused to decode received data of the another source end. In this manner,the characteristics of network coding are fully utilized, yielding morediversity gains, and greatly improving the system performance.

As shown in FIG. 10, an embodiment of the present invention provides asource end apparatus, including: a likelihood ratio demodulating module410 configured to demodulate a signal transmitted by a relay node thatis received to obtain a third log-likelihood ratio; where, the signaltransmitted by the relay node is a signal obtained after the relay nodeperforms network coding on a signal transmitted by the source endapparatus and a signal transmitted by a peer end of the source endapparatus; a likelihood ratio obtaining module 420 configured to: basedon an exclusive OR feature of network coding, perform joint processingon the third log-likelihood ratio and the first log-likelihood ratio ofthe source end apparatus to obtain a second prior log-likelihood ratioof the peer end of the source end apparatus; where, the firstlog-likelihood ratio is known, and may be obtained in advance accordingto a signal transmitted by the source end apparatus;

The specific processing method of the likelihood ratio obtaining module420 is described in detail in the method embodiment, and is notdescribed herein.

In this embodiment, because the signal sent by the source end apparatusis known to the source end apparatus, the first log-likelihood ratioLLR_(m) ₁ may be expressed as follows:

${LLR}_{m\; 1} = \left\{ \begin{matrix}{\beta,{{{if}\mspace{14mu} m_{1}} = 1}} \\{{- \beta},{{{if}\mspace{14mu} m_{1}} = 0},}\end{matrix} \right.$

where β may be a positive real number. In an embodiment, the value of βmay be 10. Certainly, in another embodiment, it may be 8. In stillanother embodiment, it may further be 6. The embodiments of the presentinvention do not restrict the value of β.

A decoding processing module 430 is configured to decode the signaltransmitted by the peer end of the source end apparatus that is receivedby using the second prior log-likelihood ratio obtained by thelikelihood ratio obtaining module 420.

It should be noted that the source end apparatus may be a base stationin an embodiment, or a terminal in another embodiment.

In an embodiment, the source end apparatus corresponding to FIG. 10 maybe used in the cooperative communications system shown in FIG. 14. Inthis case, the source end apparatus is a local end apparatus 50. It iseasily understood that as the local end apparatus 50 and a peer endapparatus 70 are symmetrical concepts. The peer end apparatus 70 has thestructure and functions similar to those of the source end apparatus.

According to the technical solution in the embodiment, for a cooperativecommunications system where a relay node adopts network coding, based onthe exclusive OR feature of network coding, a posterior log-likelihoodratio of a peer end of a source end apparatus is obtained, and theposterior log-likelihood ratio of the peer end of the source endapparatus is used to decode received data. In this manner, thecharacteristics of network coding are fully utilized, yielding morediversity gains, and greatly improving the system performance.

FIG. 11 is a schematic structural diagram of a cooperativecommunications system according to an embodiment. The system includes afirst source end 10, a second source end 20, a relay node 30, and areceiving apparatus 40.

The first source end 10 is configured to transmit a signal to the relaynode 30 and the receiving apparatus 40.

The second source end 20 is configured to transmit a signal to the relaynode 30 and the receiving apparatus 40.

The relay node 30 is configured to demodulate received signalstransmitted by the first source end and the second source end, performnetwork coding on the two demodulated signals, encode and modulate thesignals after the network coding, and send them to the receivingapparatus 40.

The receiving apparatus 40 is configured to: demodulate a signaltransmitted by the first source end that is received to obtain a firstlog-likelihood ratio; demodulate a signal transmitted by the secondsource end that is received to obtain a second log-likelihood ratio;demodulate a signal transmitted by the relay node that is received toobtain a third log-likelihood ratio; based on an exclusive OR feature ofnetwork coding, process the first log-likelihood ratio, the secondlog-likelihood ratio, and the third log-likelihood ratio to obtain aposterior log-likelihood ratio of the first source end; and decode thesignal transmitted by the first source end that is received by using theposterior log-likelihood ratio of the first source end.

Certainly, it is easily understood that the process in which thereceiving apparatus decodes the signal transmitted by the second sourceend is similar to the process in which the receiving apparatus decodesthe signal transmitted by the first source end as follows: based on theexclusive OR feature of network coding, process the first log-likelihoodratio, the second log-likelihood ratio, and the third log-likelihoodratio to obtain a posterior log-likelihood ratio of the second sourceend; and decode the signal transmitted by the second source end that isreceived by using the posterior log-likelihood ratio of the secondsource end.

The specific structure of the receiving apparatus 40 is described indetail in the apparatus embodiment, and is not described herein.

According to the technical solution in the embodiment, for a cooperativecommunications system where a relay node adopts network coding, based onthe exclusive OR feature of network coding, a posterior log-likelihoodratio of a source end is obtained, and the posterior log-likelihoodratio of the source end is used to decode received source end data. Inthis manner, the characteristics of network coding are fully utilized,yielding more diversity gains, and greatly improving the systemperformance.

Persons of ordinary skill in the art should understand that all or apart of the steps of the method according to the embodiments may beimplemented by a computer program instructing relevant hardware. Theprogram may be stored in a computer readable storage medium. When theprogram is run, the steps of the method according to the embodiments areperformed. The storage medium may be a magnetic disk, an optical disk, aread-only memory (ROM), or a random access memory (RAM).

The above are merely exemplary embodiments for illustrating the presentinvention, but the protection scope of the present invention is notlimited thereto.

What is claimed is:
 1. A receiving method in cooperative communicationscomprising: demodulating a signal transmitted by a first source end thatis received to obtain a first log-likelihood ratio; demodulating asignal transmitted by a second source end that is received to obtain asecond log-likelihood ratio; demodulating a signal transmitted by arelay node that is received to obtain a third log-likelihood ratio,wherein the signal transmitted by the relay node is a signal obtainedafter the relay node performs network coding on the signal transmittedby the first source end and the signal transmitted by the second sourceend; processing the first log-likelihood ratio, the secondlog-likelihood ratio, and the third log-likelihood ratio to obtain aposterior log-likelihood ratio of the first source end based on anexclusive OR feature of network coding; and decoding the signaltransmitted by the first source end that is received by using theposterior log-likelihood ratio of the first source end.
 2. The receivingmethod according to claim 1, wherein processing the first log-likelihoodratio, the second log-likelihood ratio, and the third log-likelihoodratio to obtain the posterior log-likelihood ratio of the first sourceend based on the exclusive OR feature of network coding comprises:performing joint processing on the second log-likelihood ratio and thethird log-likelihood ratio to obtain a prior log-likelihood ratio of thefirst source end based on the exclusive OR feature of network coding;and combining the prior log-likelihood ratio of the first source end andthe first log-likelihood ratio to obtain a posterior log-likelihoodratio of the first source end.
 3. The receiving method according toclaim 1, wherein processing the first log-likelihood ratio, the secondlog-likelihood ratio, and the third log-likelihood ratio to obtain theposterior log-likelihood ratio of the first source end based on theexclusive OR feature of network coding comprises: performing jointprocessing on the first log-likelihood ratio and the thirdlog-likelihood ratio to obtain a prior log-likelihood ratio of a secondsource end based on the exclusive OR feature of network coding;combining the prior log-likelihood ratio of the second source end andthe second log-likelihood ratio to obtain a posterior log-likelihoodratio of the second source end; performing joint processing on theposterior log-likelihood ratio of the second source end and the thirdlog-likelihood ratio to obtain a prior log-likelihood ratio of the firstsource end based on the exclusive OR feature of network coding; andcombining the prior log-likelihood ratio of the first source end and thefirst log-likelihood ratio to obtain a posterior log-likelihood ratio ofthe first source end.
 4. A receiving method in cooperativecommunications comprising: demodulating a signal transmitted by a relaynode that is received to obtain a third log-likelihood ratio, whereinthe signal transmitted by the relay node is a signal obtained after therelay node performs network coding on a signal transmitted by a localend and a signal transmitted by a peer end; performing joint processingon the third log-likelihood ratio and a first log-likelihood ratio ofthe local end to obtain a prior log-likelihood ratio of the peer endbased on the exclusive OR feature of network coding, wherein the firstlog-likelihood ratio is obtained in advance according to the signaltransmitted by the local end; and decoding the signal transmitted by therelay node that is received by using the prior log-likelihood ratio ofthe peer end to obtain a signal transmitted by the peer end.
 5. Thereceiving method in cooperative communications according to claim 4,wherein, the first log-likelihood ratio is calculated using an equation:${LLR}_{m\; 1} = \left\{ \begin{matrix}{\beta,{{{if}\mspace{14mu} m_{1}} = 1}} \\{{- \beta},{{{if}\mspace{14mu} m_{1}} = 0},}\end{matrix} \right.$ wherein LLR_(m) ₁ indicates the firstlog-likelihood ratio, wherein m₁ indicates the signal transmitted by thelocal end, and wherein β indicates a positive real number.
 6. Areceiving apparatus in cooperative communications comprising: a firstdemodulating module configured to demodulate a signal transmitted by afirst source end that is received to obtain a first log-likelihoodratio; a second demodulating module configured to demodulate a signaltransmitted by a second source end that is received to obtain a secondlog-likelihood ratio; a third demodulating module configured todemodulate a signal transmitted by a relay node that is received toobtain a third log-likelihood ratio, wherein the signal transmitted bythe relay node is a signal obtained after the relay node performsnetwork coding on the signal transmitted by the first source end and thesignal transmitted by the second source end; a processing moduleconfigured to process the first log-likelihood ratio, the secondlog-likelihood ratio, and the third log-likelihood ratio to obtain aposterior log-likelihood ratio of the first source end based on anexclusive OR feature of network coding; and a decoding module configuredto decode the signal transmitted by the first source end that isreceived by using the posterior log-likelihood ratio of the first sourceend.
 7. The receiving apparatus in cooperative communications accordingto claim 6, wherein the processing module comprises: a first processingunit configured to perform joint processing on the second log-likelihoodratio and the third log-likelihood ratio to obtain a priorlog-likelihood ratio of the first source end based on the exclusive ORfeature of network coding; and a second processing unit configured tocombine the prior log-likelihood ratio of the first source end and thefirst log-likelihood ratio to obtain a posterior log-likelihood ratio ofthe first source end.
 8. The receiving apparatus in cooperativecommunications according to claim 6, wherein the processing modulecomprises: a third processing unit configured to perform jointprocessing on the first log-likelihood ratio and the thirdlog-likelihood ratio to obtain a prior log-likelihood ratio of thesecond source end based on the exclusive OR feature of network coding; afourth processing unit configured to combine the prior log-likelihoodratio of the second source end and the second log-likelihood ratio toobtain a posterior log-likelihood ratio of the second source end; afifth processing unit configured to perform joint processing on theposterior log-likelihood ratio of the second source end and the thirdlog-likelihood ratio to obtain a prior log-likelihood ratio of the firstsource end based on the exclusive OR feature of network coding; and asixth processing unit configured to combine the prior log-likelihoodratio of the first source end and the first log-likelihood ratio toobtain a posterior log-likelihood ratio of the first source end.
 9. Asource end apparatus comprising: a likelihood ratio demodulating moduleconfigured to demodulate a signal transmitted by a relay node that isreceived to obtain a third log-likelihood ratio, wherein the signaltransmitted by the relay node is a signal obtained after the relay nodeperforms network coding on a signal transmitted by the source endapparatus and a signal transmitted by a peer end of the source endapparatus; a likelihood ratio obtaining module configured to performjoint processing on the third log-likelihood ratio and a firstlog-likelihood ratio of the source end apparatus to obtain a priorlog-likelihood ratio of the peer end of the source end apparatus basedon an exclusive OR feature of network coding, wherein the firstlog-likelihood ratio is obtained in advance according to the signaltransmitted by the source end apparatus; and a decoding processingmodule configured to decode the signal transmitted by the relay nodethat is received by using the prior log-likelihood ratio of the peer endof the source end apparatus to obtain a signal transmitted by the peerend of the source end apparatus.
 10. The apparatus according to claim 9,wherein the first log-likelihood ratio is calculated using an equation:${LLR}_{m\; 1} = \left\{ \begin{matrix}{\beta,{{{if}\mspace{14mu} m_{1}} = 1}} \\{{- \beta},{{{if}\mspace{14mu} m_{1}} = 0},}\end{matrix} \right.$ wherein LLR_(m) ₁ indicates the firstlog-likelihood ratio, wherein m₁ indicates the signal transmitted by thesource end apparatus, and wherein β indicates a positive real number.11. A cooperative communications system comprising a first source end; asecond source end; a relay node; and a receiving apparatus, wherein thefirst source node is configured to transmit a signal to the relay nodeand the receiving apparatus, wherein the second source node isconfigured to transmit a signal to the relay node and the receivingapparatus, wherein the relay node is configured to demodulate receivedsignals transmitted by the first source end and the second source end,perform network coding on the two demodulated signals, encode andmodulate the signals after the network coding, and send them to thereceiving apparatus, and wherein the receiving apparatus is configuredto demodulate a signal transmitted by the first source end that isreceived to obtain a first log-likelihood ratio, demodulate a signaltransmitted by the second source end that is received to obtain a secondlog-likelihood ratio, demodulate a signal transmitted by the relay nodethat is received to obtain a third log-likelihood ratio, process thefirst log-likelihood ratio, the second log-likelihood ratio, and thethird log-likelihood ratio to obtain a posterior log-likelihood ratio ofthe first source end based on an exclusive OR feature of network coding,and decode the signal transmitted by the first source end that isreceived by using the posterior log-likelihood ratio of the first sourceend.